--- license: cc-by-nc-4.0 task_categories: - text-generation - question-answering language: - en tags: - sql - database - query-optimization - explain-analyze - postgresql - mysql - clickhouse - cockroachdb - dba - fine-tuning pretty_name: "Enterprise Database Query Plan Optimization & Remediation Traces" size_categories: - 100 Dataset Banner

## Overview High-concurrency database workloads frequently degrade due to optimizer plan misestimations, unindexed correlated joins, merge-sort memory spills, and non-sargable expressions. This repository hosts the **Community Preview (250 verified traces)** of an architectural fine-tuning dataset spanning **PostgreSQL 16, MySQL 8.0, ClickHouse 24, CockroachDB, MariaDB, and SQLite**. Each record pairs an authentic production query regression and raw execution plan (`EXPLAIN ANALYZE`) with chain-of-thought architectural diagnosis, actionable remediation DDL, and dialect-compliant optimized queries. --- ## Dataset Splits & Commercial Licensing | Split | Records | Format | Primary Use Case | License | | :--- | :--- | :--- | :--- | :--- | | **Community Evaluation** (This Repo) | 250 | Parquet | Benchmarking, zero-shot eval, research | **CC BY-NC 4.0** | | **Enterprise Commercial Corpus** | 2,500 | Parquet + JSONL | Production fine-tuning (SFT/DPO), commercial DBA agents | **Commercial Enterprise License** | ### Complete Enterprise Corpus (2,500 Records) For production model deployment, proprietary agent training, or private RAG pipelines without non-commercial restrictions: 👉 **[Acquire Enterprise Commercial License & Dataset via Dodo Payments](https://checkout.dodopayments.com/buy/pdt_0NqD7nyGBW7fVDMd1Fm2l)** --- ## Data Structure & Schema ```json { "database_engine": "string", "slow_query": "string", "execution_plan": "string", "diagnostic_thought": "string", "remediation_ddl": "string", "optimized_query": "string" } ``` ### Field Definitions | Field | Data Type | Description | | :--- | :--- | :--- | | `database_engine` | `string` | Target engine dialect & exact version (e.g., `PostgreSQL 16.2`, `ClickHouse 24.3`). | | `slow_query` | `string` | Realistic unoptimized SQL query triggering runtime performance degradation. | | `execution_plan` | `string` | Raw optimizer output (`EXPLAIN (ANALYZE, BUFFERS)` or JSON plan) exposing node bottlenecks. | | `diagnostic_thought` | `string` | Step-by-step reasoning diagnosing node cost, row estimate deltas, and I/O buffer behavior. | | `remediation_ddl` | `string` | Executable DDL statements (`CREATE INDEX CONCURRENTLY`, table parameter tuning). | | `optimized_query` | `string` | Performant rewritten query strictly adhering to engine dialect grammar. | --- ## Quickstart (Hugging Face Datasets) ```python from datasets import load_dataset # Load Community Preview dataset = load_dataset("ayushjoshi2012/sql-optimization-diagnostic-traces", split="train") # Inspect a single diagnostic trace sample = dataset[0] print(f"Engine: {sample['database_engine']}") print(f"Slow Query:\n{sample['slow_query']}") print(f"Diagnosis:\n{sample['diagnostic_thought']}") print(f"Remediation DDL:\n{sample['remediation_ddl']}") print(f"Rewritten Query:\n{sample['optimized_query']}") ``` --- ## Core Domain Taxonomy Traces are generated across representative enterprise schema designs: * **Fintech & Ledger Core:** Double-entry ledger scans, implicit UUID-to-integer type coercion, balance aggregations. * **IoT & Telematics:** Granule skip-index mismatches, partition decompression stalls, time-bucket groupings. * **B2B SaaS & Security:** High-offset tenant audit logs, soft-delete booleans, unindexed RBAC joins. * **Healthcare & EHR:** Unindexed composite foreign keys, leading-wildcard text filters, outdated optimizer statistics. * **Freight & Global Logistics:** Disk-spilling merge joins on departure timestamps, Cartesian row multiplication. * **AdTech & Gaming Telemetry:** Unindexed streaming click joins, unbounded window function sorts, leaderboard lock contention. --- ## Citation & Contact For inquiries regarding custom synthetic domain generation, enterprise site licenses, or data additions, please commentinitiate a new discussion.